Intraoperative Imaging Modalities and Compensation for Brain Shift in Tumor Resection Surgery

Navigated Intraoperative Ultrasound Offers Effective and Efficient Real-Time Analysis of Intracranial Tumor Resection and Brain Shift

BACKGROUND AND OBJECTIVES

Neuronavigation is a fundamental tool in the resection of intracranial tumors. However, it is limited by its calibration to preoperative neuroimaging, which loses accuracy intraoperatively after brain shift. Therefore, surgeons rely on anatomic landmarks or tools like intraoperative MRI to assess the extent of tumor resection (EOR) and update neuronavigation. Recent studies demonstrate that intraoperative ultrasound (iUS) provides point-of-care imaging without the cost or resource utilization of an intraoperative MRI, and advances in neuronavigation-guided iUS provide an opportunity for real-time imaging overlaid with neuronavigation to account for brain shift. We assessed the feasibility, efficacy, and benefits of navigated iUS to assess the EOR and restore stereotactic accuracy in neuronavigation after brain shift.

METHODS

This prospective single-center study included patients presenting with intracranial tumors (gliomas, metastasis) to an academic medical center. Navigated iUS images were acquired preresection, midresection, and postresection. The EOR was determined by the surgeon intraoperatively and compared with the postoperative MRI report by an independent neuroradiologist. Outcome measures included time to perform the iUS sweep, time to process ultrasound images, and EOR predicted by the surgeon intraoperatively compared with the postoperative MRI.

RESULTS

This study included 40 patients consisting of gliomas (n = 18 high-grade gliomas, n = 4 low-grade gliomas, n = 4 recurrent) and metastasis (n = 18). Navigated ultrasound sweeps were performed in all patients (n = 83) with a median time to perform of 5.5 seconds and a median image processing time of 29.9 seconds. There was 95% concordance between the surgeon's and neuroradiologist's determination of EOR using navigated iUS and postoperative MRI, respectively. The sensitivity was 100%, and the specificity was 94%.

CONCLUSION

Navigated iUS was successfully used for EOR determination in glioma and metastasis resection. Incorporating navigated iUS into the surgical workflow is safe and efficient and provides a real-time assessment of EOR while accounting for brain shift in intracranial tumor surgeries.

A review on organ deformation modeling approaches for reliable surgical navigation using augmented reality

Augmented Reality (AR) holds the potential to revolutionize surgical procedures by allowing surgeons to visualize critical structures within the patient's body. This is achieved through superimposing preoperative organ models onto the actual anatomy. Challenges arise from dynamic deformations of organs during surgery, making preoperative models inadequate for faithfully representing intraoperative anatomy. To enable reliable navigation in augmented surgery, modeling of intraoperative deformation to obtain an accurate alignment of the preoperative organ model with the intraoperative anatomy is indispensable. Despite the existence of various methods proposed to model intraoperative organ deformation, there are still few literature reviews that systematically categorize and summarize these approaches. This review aims to fill this gap by providing a comprehensive and technical-oriented overview of modeling methods for intraoperative organ deformation in augmented reality in surgery. Through a systematic search and screening process, 112 closely relevant papers were included in this review. By presenting the current status of organ deformation modeling methods and their clinical applications, this review seeks to enhance the understanding of organ deformation modeling in AR-guided surgery, and discuss the potential topics for future advancements.

Intra-operative applications of augmented reality in glioma surgery: a systematic review

Background

Augmented reality (AR) is increasingly being explored in neurosurgical practice. By visualizing patient-specific, three-dimensional (3D) models in real time, surgeons can improve their spatial understanding of complex anatomy and pathology, thereby optimizing intra-operative navigation, localization, and resection. Here, we aimed to capture applications of AR in glioma surgery, their current status and future potential.

Methods

A systematic review of the literature was conducted. This adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline. PubMed, Embase, and Scopus electronic databases were queried from inception to October 10, 2022. Leveraging the Population, Intervention, Comparison, Outcomes, and Study design (PICOS) framework, study eligibility was evaluated in the qualitative synthesis. Data regarding AR workflow, surgical application, and associated outcomes were then extracted. The quality of evidence was additionally examined, using hierarchical classes of evidence in neurosurgery.

Results

The search returned 77 articles. Forty were subject to title and abstract screening, while 25 proceeded to full text screening. Of these, 22 articles met eligibility criteria and were included in the final review. During abstraction, studies were classified as "development" or "intervention" based on primary aims. Overall, AR was qualitatively advantageous, due to enhanced visualization of gliomas and critical structures, frequently aiding in maximal safe resection. Non-rigid applications were also useful in disclosing and compensating for intra-operative brain shift. Irrespective, there was high variance in registration methods and measurements, which considerably impacted projection accuracy. Most studies were of low-level evidence, yielding heterogeneous results.

Conclusions

AR has increasing potential for glioma surgery, with capacity to positively influence the onco-functional balance. However, technical and design limitations are readily apparent. The field must consider the importance of consistency and replicability, as well as the level of evidence, to effectively converge on standard approaches that maximize patient benefit.

Narrative Review of Multidisciplinary Management of Central Nervous Involvement in Patients with HER2-Positive Metastatic Breast Cancer: Focus on Elderly Patients

The tumor biology of human epidermal growth factor receptor 2 (HER2)-positive breast cancer (BC) promotes the development of central nervous system (CNS) metastases, with 25% of patients with HER2-positive BC developing CNS metastases. Furthermore, the incidence of HER2-positive BC brain metastases has increased in the last decades, likely because of the improved survival with targeted therapies and better detection methods. Brain metastases are detrimental to quality of life and survival and represent a challenging clinical problem, particularly in elderly women, who comprise a substantial proportion of patients diagnosed with BC and often have comorbidities or an age-related decline in organ function. Treatment options for patients with BC brain metastases include surgical resection, whole-brain radiation therapy, stereotactic radiosurgery, chemotherapy, and targeted agents. Ideally, local and systemic treatment decisions should be made by a multidisciplinary team, with input from several specialties, based on an individualized prognostic classification. In elderly patients with BC, additional age-associated conditions, such as geriatric syndromes or comorbidities, and the physiologic changes associated with aging, may impact their ability to tolerate cancer therapy and should be considered in the treatment decision-making process. This review describes the treatment options for elderly patients with HER2-positive BC and brain metastases, focusing on the importance of multidisciplinary management, the different points of view from the distinct disciplines, and the role of oncogeriatric and palliative care in this vulnerable patient group.

Simulation Method for the Physical Deformation of a Three-Dimensional Soft Body in Augmented Reality-Based External Ventricular Drainage

OBJECTIVES

Intraoperative navigation reduces the risk of major complications and increases the likelihood of optimal surgical outcomes. This paper presents an augmented reality (AR)-based simulation technique for ventriculostomy that visualizes brain deformations caused by the movements of a surgical instrument in a three-dimensional brain model. This is achieved by utilizing a position-based dynamics (PBD) physical deformation method on a preoperative brain image.

METHODS

An infrared camera-based AR surgical environment aligns the real-world space with a virtual space and tracks the surgical instruments. For a realistic representation and reduced simulation computation load, a hybrid geometric model is employed, which combines a high-resolution mesh model and a multiresolution tetrahedron model. Collision handling is executed when a collision between the brain and surgical instrument is detected. Constraints are used to preserve the properties of the soft body and ensure stable deformation.

RESULTS

The experiment was conducted once in a phantom environment and once in an actual surgical environment. The tasks of inserting the surgical instrument into the ventricle using only the navigation information presented through the smart glasses and verifying the drainage of cerebrospinal fluid were evaluated. These tasks were successfully completed, as indicated by the drainage, and the deformation simulation speed averaged 18.78 fps.

CONCLUSIONS

This experiment confirmed that the AR-based method for external ventricular drain surgery was beneficial to clinicians.

A position- and time-dependent pressure profile to model viscoelastic mechanical behavior of the brain tissue due to tumor growth

This study proposed a computational framework to calculate the resultant position- and time-dependent pressure profile on the brain tissue due to tumor growth. A finite element (FE) patch of the brain tissue was constructed and an inverse dynamic FE-optimization algorithm was used to calculate its viscoelastic mechanical properties under compressive uniaxial loading. Two patient-specific post-tumor resection FE models were input to the FE-optimization algorithm to calculate the optimized 3rd-order position-dependent and normal distribution time-dependent pressure profile parameters. The optimized viscoelastic material properties, the most suitable simulation time, and the optimized 3rd-order position- and -time-dependent pressure profiles were calculated.

A Brief Explanation on Surgical Approaches for Treatment of Different Brain Tumors

The main goal of brain tumor surgery is to achieve gross total tumor resection without postoperative complications and permanent new deficits. However, when the lesion is located close or within eloquent brain areas, cranial nerves, and/or major brain vessels, it is imperative to balance the extent of resection with the risk of harming the patient, by following a so-called maximal safe resection philosophy. This view implies a shift from an approach-guided attitude, in which few standard surgical approaches are used to treat almost all intracranial tumors, to a pathology-guided one, with surgical approaches actually tailored to the specific tumor that has to be treated with specific dedicated pre- and intraoperative tools and techniques. In this chapter, the basic principles of the most commonly used neurosurgical approaches in brain tumors surgery are presented and discussed along with an overview on all available modern tools able to improve intraoperative visualization, extent of resection, and postoperative clinical outcome.

Optimization of intraoperative ultrasound navigation during focal cortical dysplasia surgery: a case report

Intraoperative ultrasound (IUS) is known to be an effective method for neuronavigation during surgical treatment of intractable seizures caused by focal cortical dysplasia (FCD). However, the 2-dimensional (2D) IUS has poor image quality and low spatial resolution. We describe via a case report how Ultrasound integrated Brainlab (BL) – Navigation software was used to optimize 2D IUS and thereby reduce these challenges.

Case report: We present a case report of a 22-year-old female patient with a long-standing history of seizures. The patient was treated with more than two anti-epileptic drugs without any clinical efficacy. In 2022 she was diagnosed with temporal lobe FCD. We performed a temporal lobe lesionectomy using optimized IUS BL-Navigation that provided enhanced 3-dimensional (3D) images.

Discussion: The extent of resection of the underlying FCD lesion is a key factor in determining whether a patient achieves meaningful seizure freedom after surgery. While the 2D IUS offers admirable characteristics that have been used as an aid during surgery, it is our view that IUS enhanced 3D BL-Navigation offers better appreciation of FCD lesions and therefore improves the extent of resection.

Tracking motor and language eloquent white matter pathways with intraoperative fiber tracking versus preoperative tractography adjusted by intraoperative MRI-based elastic fusion

OBJECTIVE

Preoperative fiber tracking (FT) enables visualization of white matter pathways. However, the intraoperative accuracy of preoperative image registration is reduced due to brain shift. Intraoperative FT is currently considered the standard of anatomical accuracy, while intraoperative imaging can also be used to correct and update preoperative data by intraoperative MRI (ioMRI)-based elastic fusion (IBEF). However, the use of intraoperative tractography is restricted due to the need for additional acquisition of diffusion imaging in addition to scanner limitations, quality factors, and setup time. Since IBEF enables compensation for brain shift and updating of preoperative FT, the aim of this study was to compare intraoperative FT with IBEF of preoperative FT.

METHODS

Preoperative MRI (pMRI) and ioMRI, both including diffusion tensor imaging (DTI) data, were acquired between February and November 2018. Anatomy-based DTI FT of the corticospinal tract (CST) and the arcuate fascicle (AF) was reconstructed at various fractional anisotropy (FA) values on pMRI and ioMRI, respectively. The intraoperative DTI FT, as a baseline tractography, was fused with original preoperative FT and IBEF-compensated FT, processes referred to as rigid fusion (RF) and elastic fusion (EF), respectively. The spatial overlap index (Dice coefficient [DICE]) and distances of surface points (average surface distance [ASD]) of fused FT before and after IBEF were analyzed and compared in operated and nonoperated hemispheres.

RESULTS

Seventeen patients with supratentorial brain tumors were analyzed. On the operated hemisphere, the overlap index of pre- and intraoperative FT of the CST by DICE significantly increased by 0.09 maximally after IBEF. A significant decrease by 0.5 mm maximally in the fused FT presented by ASD was observed. Similar improvements were found in IBEF-compensated FT, for which AF tractography on the tumor hemispheres increased by 0.03 maximally in DICE and decreased by 1.0 mm in ASD.

CONCLUSIONS

Preoperative tractography after IBEF is comparable to intraoperative tractography and can be a reliable alternative to intraoperative FT.

Surgery of Motor Eloquent Glioblastoma Guided by TMS-Informed Tractography: Driving Resection Completeness Towards Prolonged Survival

Background

Surgical treatment of patients with glioblastoma affecting motor eloquent brain regions remains critically discussed given the risk–benefit dilemma of prolonging survival at the cost of motor-functional damage. Tractography informed by navigated transcranial magnetic stimulation (nTMS-informed tractography, TIT) provides a rather robust estimate of the individual location of the corticospinal tract (CST), a highly vulnerable structure with poor functional reorganisation potential. We hypothesised that by a more comprehensive, individualised surgical decision-making using TIT, tumours in close relationship to the CST can be resected with at least equal probability of gross total resection (GTR) than less eloquently located tumours without causing significantly more gross motor function harm. Moreover, we explored whether the completeness of TIT-aided resection translates to longer survival.

Methods

A total of 61 patients (median age 63 years, m = 34) with primary glioblastoma neighbouring or involving the CST were operated on between 2010 and 2015. TIT was performed to inform surgical planning in 35 of the patients (group T; vs. 26 control patients). To achieve largely unconfounded group comparisons for each co-primary outcome (i.e., gross-motor functional worsening, GTR, survival), (i) uni- and multivariate regression analyses were performed to identify features of optimal outcome prediction; (ii), optimal propensity score matching (PSM) was applied to balance those features pairwise across groups, followed by (iii) pairwise group comparison.

Results

Patients in group T featured a significantly higher lesion-CST overlap compared to controls (8.7 ± 10.7% vs. 3.8 ± 5.7%; p = 0.022). The frequency of gross motor worsening was higher in group T, albeit non-significant (n = 5/35 vs. n = 0/26; p = 0.108). PSM-based paired-sample comparison, controlling for the confounders of preoperative tumour volume and vicinity to the delicate vasculature of the insula, showed higher GTR rates in group T (77% vs. 69%; p = 0.025), particularly in patients with a priori intended GTR (87% vs. 78%; p = 0.003). This translates into a prolonged PFS in the same PSM subgroup (8.9 vs. 5.8 months; p = 0.03), with GTR representing the strongest predictor of PFS (p = 0.001) and OS (p = 0.0003) overall.

Conclusion

The benefit of TIT-aided GTR appears to overcome the drawbacks of potentially elevated motor functional risk in motor eloquent tumour localisation, leading to prolonged survival of patients with primary glioblastoma close to the CST.

Pose Estimation and Non-Rigid Registration for Augmented Reality During Neurosurgery

OBJECTIVE

A craniotomy is the removal of a part of the skull to allow surgeons to have access to the brain and treat tumors. When accessing the brain, a tissue deformation occurs and can negatively influence the surgical procedure outcome. In this work, we present a novel Augmented Reality neurosurgical system to superimpose pre-operative 3D meshes derived from MRI onto a view of the brain surface acquired during surgery.

METHODS

Our method uses cortical vessels as main features to drive a rigid then non-rigid 3D/2D registration. We first use a feature extractor network to produce probability maps that are fed to a pose estimator network to infer the 6-DoF rigid pose. Then, to account for brain deformation, we add a non-rigid refinement step formulated as a Shape-from-Template problem using physics-based constraints that helps propagate the deformation to sub-cortical level and update tumor location.

RESULTS

We tested our method retrospectively on 6 clinical datasets and obtained low pose error, and showed using synthetic dataset that considerable brain shift compensation and low TRE can be achieved at cortical and sub-cortical levels.

CONCLUSION

The results show that our solution achieved accuracy below the actual clinical errors demonstrating the feasibility of practical use of our system.

SIGNIFICANCE

This work shows that we can provide coherent Augmented Reality visualization of 3D cortical vessels observed through the craniotomy using a single camera view and that cortical vessels provide strong features for performing both rigid and non-rigid registration.

Towards real-time intraoperative tissue interrogation for REIMS-guided glioma surgery

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REIMS can differentiate glioblastoma from normal brain with 99.2% sensitivity.

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Starting from 5% glioblastoma, REIMS showed a 100% correct classification rate.

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Low-grade gliomas can be identified with a 97.5% sensitivity.

Introduction

Objectives

Methods

Results

Conclusion

Photoacoustic-MR Image Registration Based on a Co-Sparse Analysis Model to Compensate for Brain Shift

Brain shift is an important obstacle to the application of image guidance during neurosurgical interventions. There has been a growing interest in intra-operative imaging to update the image-guided surgery systems. However, due to the innate limitations of the current imaging modalities, accurate brain shift compensation continues to be a challenging task. In this study, the application of intra-operative photoacoustic imaging and registration of the intra-operative photoacoustic with pre-operative MR images are proposed to compensate for brain deformation. Finding a satisfactory registration method is challenging due to the unpredictable nature of brain deformation. In this study, the co-sparse analysis model is proposed for photoacoustic-MR image registration, which can capture the interdependency of the two modalities. The proposed algorithm works based on the minimization of mapping transform via a pair of analysis operators that are learned by the alternating direction method of multipliers. The method was evaluated using an experimental phantom and ex vivo data obtained from a mouse brain. The results of the phantom data show about 63% improvement in target registration error in comparison with the commonly used normalized mutual information method. The results proved that intra-operative photoacoustic images could become a promising tool when the brain shift invalidates pre-operative MRI.

Second window ICG predicts postoperative MRI gadolinium enhancement in high grade gliomas and brain metastases

A prospective trial evaluating the utility of second window indocyanine green (SWIG) in predicting postoperative MRI gadolinium enhancement was performed on high-grade gliomas (HGGs) and brain metastases. Compared to white light alone, SWIG demonstrated a higher sensitivity, negative predictive value, and accuracy in predicting residual neoplasm on MRI. The specificity of SWIG for predicting MRI enhancement was higher in HGGs than brain metastases. Clinically, near-infrared (NIR) imaging was better able to predict tumor recurrence than postoperative MRI. These results illustrate how SWIG is able to take advantage of gadolinium-like distribution properties to extravasate into the tumor microenvironment, enabling guidance in surgical resection.

The video can be found here: https://stream.cadmore.media/r10.3171/2021.10.FOCVID21204

Inverse dynamic finite element-optimization modeling of the brain tumor mass-effect using a variable pressure boundary

BACKGROUND AND OBJECTIVE

Statistical atlases of brain structure can potentially contribute in the surgical and radiotherapeutic treatment planning for the brain tumor patients. However, the current brain image-registration methods lack of accuracy when it comes to the mass-effect caused by tumor growth. Numerical simulations, such as finite element method (FEM), allow us to calculate the resultant pressure and deformation in the brain tissue due to tumor growth, and to predict the mass-effect. To date, however, the pressure boundary in the brain tissue due to tumor growth has been simply presented as a constant profile throughout the entire tumor outer surface that resulted in discrepancy between the patient imaging data and brain atlases.

METHODS

In this study, we employed a fully-coupled inverse dynamic FE-optimization method to estimate the resultant variable pressure boundary due to tumor resection surgery. To do that, magnetic resonance imaging data of two patients' pre- and post-tumor resection surgery were registered, segmented, volume-meshed, and prepared for fully-coupled inverse dynamic FE-optimization simulations. Two different pressure boundaries were defined on the brain cavity after tumor resection including: a) a constant pressure boundary and b) a variable pressure boundary. The inverse FE-optimization algorithm was used to find the optimum constant and variable pressure boundaries that result in the least distance between the surface-nodes of the post-surgery brain cavity and pre-surgery tumor.

RESULTS

The results revealed that a variable pressure boundary causes a considerably lower mean percentage error compared to a constant pressure one; hence, it can more effectively address the realistic boundary in tumor resection surgery and predict the mass-effect.

CONCLUSIONS

The proposed variable pressure boundary can be a robust tool that allows batch processing to register the brains with tumors to statistical atlases of normal brains and construction of brain tumor atlases. This approach is also computationally inexpensive and can be coupled to any FE software to run. The findings of this study have implications for not only predicting the accurate pressure boundary and mass-effect before tumor resection surgery, but also for predicting some clinical symptoms of brain cancers and presenting useful tools for APPLICATIONs in image-guided neurosurgery.

Viscoelastic biomechanical models to predict inward brain-shift using public benchmark data

Brain-shift during neurosurgery compromises the accuracy of tracking the boundaries of the tumor to be resected. Although several studies have used various finite element models (FEMs) to predict inward brain-shift, evaluation of their accuracy and efficiency based on public benchmark data has been limited. This study evaluates several FEMs proposed in the literature (various boundary conditions, mesh sizes, and material properties) by using intraoperative imaging data (the public REtroSpective Evaluation of Cerebral Tumors [RESECT] database). Four patients with low-grade gliomas were identified as having inward brain-shifts. We computed the accuracy (using target registration error) of several FEM-based brain-shift predictions and compared our findings. Since information on head orientation during craniotomy is not included in this database, we tested various plausible angles of head rotation. We analyzed the effects of brain tissue viscoelastic properties, mesh size, craniotomy position, CSF drainage level, and rigidity of meninges and then quantitatively evaluated the trade-off between accuracy and central processing unit time in predicting inward brain-shift across all models with second-order tetrahedral FEMs. The mean initial target registration error (TRE) was 5.78 ± 3.78 mm with rigid registration. FEM prediction (edge-length, 5 mm) with non-rigid meninges led to a mean TRE correction of 1.84 ± 0.83 mm assuming heterogeneous material. Results show that, for the low-grade glioma patients in the study, including non-rigid modeling of the meninges was significant statistically. In contrast including heterogeneity was not significant. To estimate the optimal head orientation and CSF drainage, an angle step of 5° and an CSF height step of 5 mm were enough leading to <0.26 mm TRE fluctuation.

Utilizing Intraoperative Navigated 3D Color Doppler Ultrasound in Glioma Surgery

Background

In glioma surgery, the patient’s outcome is dramatically influenced by the extent of resection and residual tumor volume. To facilitate safe resection, neuronavigational systems are routinely used. However, due to brain shift, accuracy decreases with the course of the surgery. Intraoperative ultrasound has proved to provide excellent live imaging, which may be integrated into the navigational procedure. Here we describe the visualization of vascular landmarks and their shift during tumor resection using intraoperative navigated 3D color Doppler ultrasound (3D iUS color Doppler).

Methods

Six patients suffering from glial tumors located in the temporal lobe were included in this study. Intraoperative computed tomography was used for registration. Datasets of 3D iUS color Doppler were generated before dural opening and after tumor resection, and the vascular tree was segmented manually. In each dataset, one to four landmarks were identified, compared to the preoperative MRI, and the Euclidean distance was calculated.

Results

Pre-resectional mean Euclidean distance of the marked points was 4.1 ± 1.3 mm (mean ± SD), ranging from 2.6 to 6.0 mm. Post-resectional mean Euclidean distance was 4.7. ± 1.0 mm, ranging from 2.9 to 6.0 mm.

Conclusion

3D iUS color Doppler allows estimation of brain shift intraoperatively, thus increasing patient safety. Future implementation of the reconstructed vessel tree into the navigational setup might allow navigational updating with further consecutive increasement of accuracy.

Electromagnetic Navigation Systems and Intraoperative Neuromonitoring: Reliability and Feasibility Study

BACKGROUND

A recent influx of intraoperative technology is being used in neurosurgery, but few reports investigate the accuracy and safety of these technologies when used simultaneously.

OBJECTIVE

To assess the ability to use an electromagnetic navigation system alongside multimodal intraoperative neurophysiological monitoring (IONM).

METHODS

Single-institution prospective cohort study of patients requiring craniotomy for brain tumor resection operated using an electromagnetic navigation system (AxiEM, Medtronic®). motor evoked potentials, somatosensory evoked potentials (SSEPs), electroencephalography, and electromyography were recorded and analyzed with AxiEM on (with/without filters) and off. The neurological outcomes of the patients were recorded.

RESULTS

A total of 15 patients were included (8 males/7 females, mean age 52.13 yr). Even though the raw acquisition is affected by the electromagnetic field (particularly SSEPs), no significant difference was detected in the morphology, amplitude, and latency of the different monitoring modalities (AxiEM off vs on) after the appropriate software filter application. Adjustments to the frequency of SSEP stimulation and number of averages, and reductions to the low-pass filters were applied. Notch filters were used appropriately and changes to the physical setup of the IONM and electromagnetic navigation system equipment reduced noise. Postoperatively, none of the patients developed new focal deficits; 7 patients showed improvement in their motor deficit (4 recovered fully).

CONCLUSION

The information provided by the IONM in intracranial neurosurgery patients whilst also using electromagnetic navigation systems is reliable for monitoring, mapping, and detecting intraoperative complications, provided that the appropriate software filters and tools are applied.

Intraoperative contrast-enhanced ultrasound for intramedullary spinal neoplasms: patient series

BACKGROUND

Primary intramedullary spinal tumors cause significant morbidity and death. Intraoperative ultrasound as an adjunct for localization and monitoring the extent of resection has not been systematically evaluated in these patients; the effectiveness of intraoperative contrast-enhanced ultrasound (CEUS) remains almost completely unexplored.

OBSERVATIONS

A retrospective case series of patients at a single institution who had consented to the off-label use of intraoperative CEUS was identified. Seven patients with a mean age of 52.8 ± 15.8 years underwent resection of intramedullary tumors assisted by CEUS performed by a single attending neurosurgeon. Histopathological evaluation revealed 3 cases of hemangioblastoma, 1 case of pilocytic astrocytoma, 2 cases of ependymoma, and 1 case of subependymoma. Contrast enhancement correlated with gadolinium enhancement on preoperative magnetic resonance imaging. Intraoperative CEUS facilitated precise lesion localization and myelotomy planning. Dynamic CEUS studies were useful in demonstrating the blood supply to lesions with a dominant vascular pedicle. Regardless of contrast uptake, the differential enhancement between spinal cord tissue and neoplasm assisted in determining interface boundaries.

LESSONS

Intraoperative CEUS constitutes a useful adjunct for the intraoperative delineation of contrast-enhancing intramedullary tumors and in vivo confirmation of gross-total resection. Systematic investigation is needed to establish the role of CEUS for resection of intramedullary spinal tumors of various pathologies.

Shear wave elastography for intracranial epidermoid tumors

BACKGROUND

Ultrasound elastography (USE) is a novel technique that assesses the mechanical properties of body tissues in real time. Based on elasticity measurements, USE enables the differentiation of tumor tissue from surrounding normal tissue.

OBJECTIVES

We aimed to evaluate an intraoperative SWE technique for differentiating tumor tissue (epidermoid cyst) from the surrounding normal brain tissue based on elastic properties.

METHODS

We prospectively report the intraoperative elasticity assessments of four patients diagnosed with epidermoid cysts. Along with standard ultrasonography, intraoperative shear wave elastography (SWE) was used to identify tumor tissue and assess the elasticity of each tumor and the surrounding normal brain.

RESULTS

USE enabled the differentiation between epidermoid cysts and the surrounding normal brain tissue in real time intraoperatively; visual data (SWE elasticity map) and quantitative data (elasticity measurements in kilopascals) were utilized to identify the epidermoid cyst based on its elastic properties. The area representing the epidermoid cyst had an increased elasticity on SWE view and high mean elasticity values (193.7 ± 70.9 kPa in case 1, 168 ± 24.5 kPa in case 2, 205.1 ± 6.7 kPa in case 3, and 101.3 ± 12.6 kPa in case 4). The area representing the adjacent normal brain tissue on SWE view had lower mean elasticity values (14.9 ± 1.9 kPa in case 1, 22.6 ± 8.3 kPa in case 2, and 23.8 ± 1.4 kPa in case 4).

CONCLUSION

This study demonstrates the feasibility and promising value of SWE as an intraoperative tool during epidermoid cyst resection. Epidermoid tissue remnants that are hidden from the microscopic view can be detected using SWE.

Navigated 3D Ultrasound in Brain Metastasis Surgery: Analyzing the Differences in Object Appearances in Ultrasound and Magnetic Resonance Imaging

Background: Implementation of intraoperative 3D ultrasound (i3D US) into modern neuronavigational systems offers the possibility of live imaging and subsequent imaging updates. However, different modalities, image acquisition strategies, and timing of imaging influence object appearances. We analyzed the differences in object appearances in ultrasound (US) and magnetic resonance imaging (MRI) in 35 cases of brain metastasis, which were operated in a multimodal navigational setup after intraoperative computed tomography based (iCT) registration. Method: Registration accuracy was determined using the target registration error (TRE). Lesions segmented in preoperative magnetic resonance imaging (preMRI) and i3D US were compared focusing on object size, location, and similarity. Results: The mean and standard deviation (SD) of the TRE was 0.84 ± 0.36 mm. Objects were similar in size (mean ± SD in preMRI: 13.6 ± 16.0 cm3 vs. i3D US: 13.5 ± 16.0 cm3). The Dice coefficient was 0.68 ± 0.22 (mean ± SD), the Hausdorff distance 8.1 ± 2.9 mm (mean ± SD), and the Euclidean distance of the centers of gravity 3.7 ± 2.5 mm (mean ± SD). Conclusion: i3D US clearly delineates tumor boundaries and allows live updating of imaging for compensation of brain shift, which can already be identified to a significant amount before dural opening.

Detecting small conflicting drainages with contrast-enhanced magnetic resonance venography for surgical planning: a technical description and quantified analysis

BACKGROUND

Recent studies have shown the challenges involved in detecting small conflicting vessels (1.0-1.5 mm) on contrast-enhanced (CE) T1 images during stereoelectroencephalography (SEEG) planning. Improving the resolution of non-invasive approaches to identify these vessels is possible and important. We present a superior sagittal sinus mapping-based CE-magnetic resonance venography (CE-MRV) protocol calibrated by craniotomies.

METHOD

Seven patients with epileptic symptoms who received craniotomy were enrolled. CE-MRV was acquired with a bolus mapping of the superior sagittal sinus. Together with the T1 image, 3D veins and the brain surface were visualized. The resolution of the CE-MRV was quantified by measuring the diameter of superficial drainages after exposure of the brain surface during craniotomy.

RESULTS

A total of 37 superficial drainages were exposed in the bone windows. CE-MRV visualized all these drainages. On average, one superficial drainage could be found in every 13.2 mm diameter of the bone window. The boundary resolution of the CE-MRV was 0.58-0.8 mm in vessel diameter, while drainages larger than 0.8 mm were visualized consistently.

CONCLUSIONS

The resolution of the CE-MRV in the present study met the requirement for detection of small conflicting vessels during SEEG planning. The visualized venous landmarks could be used for visual guidance to the surgical zone. As a non-invasive approach, CE-MRV is practical to use in the clinical setting.

Deformation Aware Augmented Reality for Craniotomy using 3D/2D Non-rigid Registration of Cortical Vessels

Intra-operative brain shift is a well-known phenomenon that describes non-rigid deformation of brain tissues due to gravity and loss of cerebrospinal fluid among other phenomena. This has a negative influence on surgical outcome that is often based on pre-operative planning where the brain shift is not considered. We present a novel brain-shift aware Augmented Reality method to align pre-operative 3D data onto the deformed brain surface viewed through a surgical microscope. We formulate our non-rigid registration as a Shape-from-Template problem. A pre-operative 3D wire-like deformable model is registered onto a single 2D image of the cortical vessels, which is automatically segmented. This 3D/2D registration drives the underlying brain structures, such as tumors, and compensates for the brain shift in sub-cortical regions. We evaluated our approach on simulated and real data composed of 6 patients. It achieved good quantitative and qualitative results making it suitable for neurosurgical guidance.

Physical Plasticity of the Brain and Deep Brain Stimulation Lead: Evolution in the First Post-operative Week

Background: Deep brain stimulation (DBS) is a therapy for movement disorders and psychiatric conditions. In the peri-operative period, brain shift occurs as the consequence of events related to the brain surgery which results in post-operative lead deformation. Objective: To quantify post-operative 3-dimensional DBS lead deformation after implantation. Methods: In 13 patients who had DBS lead implantation, we performed preoperative magnetic resonance imaging (MRI), preoperative computed tomography (CT) scans after placement of fiducial markers, and post-operative CT scans immediately, 24-48 h, and 7 days after implantation. The MRI scans were used to define brain orientation and merged with CT scans. Lead deviation was determined relative to a theoretical linear lead path defined by the skull entry and target lead tip points. Results: In the sagittal plane, we distinguished an initial period after surgery (<48 h) characterized by a deviation of the lead toward the rostral direction and a late period (over 1 week) characterized by a lead deviation toward the caudal direction. In the coronal plane, there was higher probability of lead deviation in the lateral than medial direction. During 7 days after implantation, there was net movement of the center of the lead anteriorly, and the half of the lead close to the entry point moved medially. These deviations appeared normative since all patients included in this study had benefits from DBS therapy with total power of charged comparable to those described in literature. Conclusion: DBS lead deviation occurs during 7 days after implantation. The range of deviation described in this study was not associated to adverse clinical effects and may be considered normative. Future multicenter studies would be helpful to define guide lines on DBS lead deformation and its contribution to clinical outcome.

Shift in electrocorticography electrode locations after surgical implantation in children

Interpreting electrocorticography (ECoG) in the context of neuroimaging requires that multimodal information be integrated accurately. However, the implantation of ECoG electrodes can shift the brain impacting the spatial interpretation of electrode locations in the context of pre-implant imaging. We characterized the amount of shift in ECoG electrode locations immediately after implant in a pediatric population. Electrode-shift was quantified as the difference in the electrode locations immediately after surgery (via post-operation CT) compared to the brain surface before the operation (pre-implant T1 MRI). A total of 1140 ECoG contracts were assessed across 18 patients ranging from 3 to 19 (12.1 ± 4.8) years of age who underwent intracranial monitoring in preparation for epilepsy resection surgery. Patients had an average of 63 channels assessed with an average of 5.64 ± 3.27 mm shift from the pre-implant brain surface within 24 h of implant. This shift significantly increased with estimated intracranial volume, but not age. Shift also varied significantly depending of the lobe the contact was over; where contacts on the temporal and frontal lobe had less shift than the parietal. Furthermore, contacts on strips had significantly less shift than those on grids. The shift in the brain surface due to ECoG implantation could lead to a misinterpretation of contact location particularly in patients with larger intracranial volume and for grid contacts over the parietal lobes.

Accounting for intraoperative brain shift ascribable to cavity collapse during intracranial tumor resection

Purpose: For many patients with intracranial tumors, accurate surgical resection is a mainstay of their treatment paradigm. During surgical resection, image guidance is used to aid in localization and resection. Intraoperative brain shift can invalidate these guidance systems. One cause of intraoperative brain shift is cavity collapse due to tumor resection, which will be referred to as "debulking." We developed an imaging-driven finite element model of debulking to create a comprehensive simulation data set to reflect possible intraoperative changes. The objective was to create a method to account for brain shift due to debulking for applications in image-guided neurosurgery. We hypothesized that accounting for tumor debulking in a deformation atlas data framework would improve brain shift predictions, which would enhance image-based surgical guidance. Approach: This was evaluated in a six-patient intracranial tumor resection intraoperative data set. The brain shift deformation atlas data framework consisted of n = 756 simulated deformations to account for effects due to gravity-induced and hyperosmotic drug-induced brain shift, which reflects previous developments. An additional complement of n = 84 deformations involving simulated tumor growth followed by debulking was created to capture observed intraoperative effects not previously included. Results: In five of six patient cases evaluated, inclusion of debulking mechanics improved brain shift correction by capturing global mass effects resulting from the resected tumor. Conclusions: These findings suggest imaging-driven brain shift models used to create a deformation simulation data framework of observed intraoperative events can be used to assist in more accurate image-guided surgical navigation in the brain.

Automatic segmentation of brain tumor resections in intraoperative ultrasound images using U-Net

To compensate for the intraoperative brain tissue deformation, computer-assisted intervention methods have been used to register preoperative magnetic resonance images with intraoperative images. In order to model the deformation due to tissue resection, the resection cavity needs to be segmented in intraoperative images. We present an automatic method to segment the resection cavity in intraoperative ultrasound (iUS) images. We trained and evaluated two-dimensional (2-D) and three-dimensional (3-D) U-Net networks on two datasets of 37 and 13 cases that contain images acquired from different ultrasound systems. The best overall performing method was the 3-D network, which resulted in a 0.72 mean and 0.88 median Dice score over the whole dataset. The 2-D network also had good results with less computation time, with a median Dice score over 0.8. We also evaluated the sensitivity of network performance to training and testing with images from different ultrasound systems and image field of view. In this application, we found specialized networks to be more accurate for processing similar images than a general network trained with all the data. Overall, promising results were obtained for both datasets using specialized networks. This motivates further studies with additional clinical data, to enable training and validation of a clinically viable deep-learning model for automated delineation of the tumor resection cavity in iUS images.

Predicted Microscopic Cortical Brain Images for Optimal Craniotomy Positioning and Visualization

During a craniotomy, the skull is opened to allow surgeons to have access to the brain and perform the procedure. The position and size of this opening are chosen in a way to avoid critical structures, such as vessels, and facilitate the access to tumors. Planning the operation is done based on pre-operative images and does not account for intra-operative surgical events. We present a novel image-guided neurosurgical system to optimize the craniotomy opening. Using physics-based modeling we define a cortical deformation map that estimates the displacement field at candidate craniotomy locations. This deformation map is coupled with an image analogy algorithm that produces realistic synthetic images that can be used to predict both the geometry and the appearance of the brain surface before opening the skull. These images account for cortical vessel deformations that may occur after opening the skull and is rendered in a way that increases the surgeon's understanding and assimilation. Our method was tested retrospectively on patients data showing good results and demonstrating the feasibility of practical use of our system.

Demonstrative study of brain anatomical landmarks by intraoperative ultrasound imaging

Objectives

Intraoperative use of ultrasound in brain surgery needs good understanding of the brain anatomy in ultrasound images. This study aims to compare ultrasound imaging of brain anatomical landmarks during surgery to perioperative computed tomography (CT), and perioperative magnetic resonance imaging (MRI) as demonstration for encouraging usage as low cost, available and hazardless device.

Methods

In total; 350 patients were subjected to brain surgeries under ultrasound guidance using 2.5–8 megahertz (MHZ) transducers, at neurosurgery department Zagazig university hospital from January 2012 to January 2019. Brain anatomical landmarks were compared between ultrasound images, and perioperative images for safe, and confident surgeries.

Results

Various intracranial anatomical landmarks could be well-demonstrated by ultrasound through the open fontanel, or once the skull was opened, and during surgical work in real time fashion, facilitating surgical procedures, and avoiding complications.

Conclusion

Real-time ultrasound is of great help during brain surgeries in delineating brain anatomical landmarks as well as MRI, and CT brain. The growing learning standard of intraoperative ultrasound (IOUS) use makes brain surgery more simple with avoiding brain shift problems, radiation exposure, and high cost of other intraoperative modalities.

A comparison of thin-plate spline deformation and finite element modeling to compensate for brain shift during tumor resection

PURPOSE

Brain shift during tumor resection can progressively invalidate the accuracy of neuronavigation systems and affect neurosurgeons' ability to achieve optimal resections. This paper compares two methods that have been presented in the literature to compensate for brain shift: a thin-plate spline deformation model and a finite element method (FEM). For this comparison, both methods are driven by identical sparse data. Specifically, both methods are driven by displacements between automatically detected and matched feature points from intraoperative 3D ultrasound (iUS). Both methods have been shown to be fast enough for intraoperative brain shift correction (Machado et al. in Int J Comput Assist Radiol Surg 13(10):1525-1538, 2018; Luo et al. in J Med Imaging (Bellingham) 4(3):035003, 2017). However, the spline method requires no preprocessing and ignores physical properties of the brain while the FEM method requires significant preprocessing and incorporates patient-specific physical and geometric constraints. The goal of this work was to explore the relative merits of these methods on recent clinical data.

METHODS

Data acquired during 19 sequential tumor resections in Brigham and Women's Hospital's Advanced Multi-modal Image-Guided Operating Suite between December 2017 and October 2018 were considered for this retrospective study. Of these, 15 cases and a total of 24 iUS to iUS image pairs met inclusion requirements. Automatic feature detection (Machado et al. in Int J Comput Assist Radiol Surg 13(10):1525-1538, 2018) was used to detect and match features in each pair of iUS images. Displacements between matched features were then used to drive both the spline model and the FEM method to compensate for brain shift between image acquisitions. The accuracies of the resultant deformation models were measured by comparing the displacements of manually identified landmarks before and after deformation.

RESULTS

The mean initial subcortical registration error between preoperative MRI and the first iUS image averaged 5.3 ± 0.75 mm. The mean subcortical brain shift, measured using displacements between manually identified landmarks in pairs of iUS images, was 2.5 ± 1.3 mm. Our results showed that FEM was able to reduce subcortical registration error by a small but statistically significant amount (from 2.46 to 2.02 mm). A large variability in the results of the spline method prevented us from demonstrating either a statistically significant reduction in subcortical registration error after applying the spline method or a statistically significant difference between the results of the two methods.

CONCLUSIONS

In this study, we observed less subcortical brain shift than has previously been reported in the literature (Frisken et al., in: Miller (ed) Biomechanics of the brain, Springer, Cham, 2019). This may be due to the fact that we separated out the initial misregistration between preoperative MRI and the first iUS image from our brain shift measurements or it may be due to modern neurosurgical practices designed to reduce brain shift, including reduced craniotomy sizes and better control of intracranial pressure with the use of mannitol and other medications. It appears that the FEM method and its use of geometric and biomechanical constraints provided more consistent brain shift correction and better correction farther from the driving feature displacements than the simple spline model. The spline-based method was simpler and tended to give better results for small deformations. However, large variability in the spline results and relatively small brain shift prevented this study from demonstrating a statistically significant difference between the results of the two methods.

Registration of vascular structures using a hybrid mixture model

PURPOSE

Morphological changes to anatomy resulting from invasive surgical procedures or pathology, typically alter the surrounding vasculature. This makes it useful as a descriptor for feature-driven image registration in various clinical applications. However, registration of vasculature remains challenging, as vessels often differ in size and shape, and may even miss branches, due to surgical interventions or pathological changes. Furthermore, existing vessel registration methods are typically designed for a specific application. To address this limitation, we propose a generic vessel registration approach useful for a variety of clinical applications, involving different anatomical regions.

METHODS

A probabilistic registration framework based on a hybrid mixture model, with a refinement mechanism to identify missing branches (denoted as HdMM+) during vasculature matching, is introduced. Vascular structures are represented as 6-dimensional hybrid point sets comprising spatial positions and centerline orientations, using Student's t-distributions to model the former and Watson distributions for the latter.

RESULTS

The proposed framework is evaluated for intraoperative brain shift compensation, and monitoring changes in pulmonary vasculature resulting from chronic lung disease. Registration accuracy is validated using both synthetic and patient data. Our results demonstrate, HdMM+ is able to reduce more than [Formula: see text] of the initial error for both applications, and outperforms the state-of-the-art point-based registration methods such as coherent point drift and Student's t-distribution mixture model, in terms of mean surface distance, modified Hausdorff distance, Dice and Jaccard scores.

CONCLUSION

The proposed registration framework models complex vascular structures using a hybrid representation of vessel centerlines, and accommodates intricate variations in vascular morphology. Furthermore, it is generic and flexible in its design, enabling its use in a variety of clinical applications.

Effects of surgical targeting in laser interstitial thermal therapy for mesial temporal lobe epilepsy: A multicenter study of 234 patients

OBJECTIVE

Laser interstitial thermal therapy (LITT) for mesial temporal lobe epilepsy (mTLE) has reported seizure freedom rates between 36% and 78% with at least 1 year of follow-up. Unfortunately, the lack of robust methods capable of incorporating the inherent variability of patient anatomy, the variability of the ablated volumes, and clinical outcomes have limited three-dimensional quantitative analysis of surgical targeting and its impact on seizure outcomes. We therefore aimed to leverage a novel image-based methodology for normalizing surgical therapies across a large multicenter cohort to quantify the effects of surgical targeting on seizure outcomes in LITT for mTLE.

METHODS

This multicenter, retrospective cohort study included 234 patients from 11 centers who underwent LITT for mTLE. To investigate therapy location, all ablation cavities were manually traced on postoperative magnetic resonance imaging (MRI), which were subsequently nonlinearly normalized to a common atlas space. The association of clinical variables and ablation location to seizure outcome was calculated using multivariate regression and Bayesian models, respectively.

RESULTS

Ablations including more anterior, medial, and inferior temporal lobe structures, which involved greater amygdalar volume, were more likely to be associated with Engel class I outcomes. At both 1 and 2 years after LITT, 58.0% achieved Engel I outcomes. A history of bilateral tonic-clonic seizures decreased chances of Engel I outcome. Radiographic hippocampal sclerosis was not associated with seizure outcome.

SIGNIFICANCE

LITT is a viable treatment for mTLE in patients who have been properly evaluated at a comprehensive epilepsy center. Consideration of surgical factors is imperative to the complete assessment of LITT. Based on our model, ablations must prioritize the amygdala and also include the hippocampal head, parahippocampal gyrus, and rhinal cortices to maximize chances of seizure freedom. Extending the ablation posteriorly has diminishing returns. Further work is necessary to refine this analysis and define the minimal zone of ablation necessary for seizure control.

Preliminary Results Comparing Thin Plate Splines with Finite Element Methods for Modeling Brain Deformation during Neurosurgery using Intraoperative Ultrasound

Brain shift compensation attempts to model the deformation of the brain which occurs during the surgical removal of brain tumors to enable mapping of presurgical image data into patient coordinates during surgery and thus improve the accuracy and utility of neuro-navigation. We present preliminary results from clinical tumor resections that compare two methods for modeling brain deformation, a simple thin plate spline method that interpolates displacements and a more complex finite element method (FEM) that models physical and geometric constraints of the brain and its material properties. Both methods are driven by the same set of displacements at locations surrounding the tumor. These displacements were derived from sets of corresponding matched features that were automatically detected using the SIFT-Rank algorithm. The deformation accuracy was tested using a set of manually identified landmarks. The FEM method requires significantly more preprocessing than the spline method but both methods can be used to model deformations in the operating room in reasonable time frames. Our preliminary results indicate that the FEM deformation model significantly out-performs the spline-based approach for predicting the deformation of manual landmarks. While both methods compensate for brain shift, this work suggests that models that incorporate biophysics and geometric constraints may be more accurate.

Using the variogram for vector outlier screening: application to feature-based image registration

PURPOSE

Matching points that are derived from features or landmarks in image data is a key step in some medical imaging applications. Since most robust point matching algorithms claim to be able to deal with outliers, users may place high confidence in the matching result and use it without further examination. However, for tasks such as feature-based registration in image-guided neurosurgery, even a few mismatches, in the form of invalid displacement vectors, could cause serious consequences. As a result, having an effective tool by which operators can manually screen all matches for outliers could substantially benefit the outcome of those applications.

METHODS

We introduce a novel variogram-based outlier screening method for vectors. The variogram is a powerful geostatistical tool for characterizing the spatial dependence of stochastic processes. Since the spatial correlation of invalid displacement vectors, which are considered as vector outliers, tends to behave differently than normal displacement vectors, they can be efficiently identified on the variogram.

RESULTS

We validate the proposed method on 9 sets of clinically acquired ultrasound data. In the experiment, potential outliers are flagged on the variogram by one operator and further evaluated by 8 experienced medical imaging researchers. The matching quality of those potential outliers is approximately 1.5 lower, on a scale from 1 (bad) to 5 (good), than valid displacement vectors.

CONCLUSION

The variogram is a simple yet informative tool. While being used extensively in geostatistical analysis, it has not received enough attention in the medical imaging field. We believe there is a good deal of potential for clinically applying the proposed outlier screening method. By way of this paper, we also expect researchers to find variogram useful in other medical applications that involve motion vectors analyses.

Experimental study of sector and linear array ultrasound accuracy and the influence of navigated 3D-reconstruction as compared to MRI in a brain tumor model

PURPOSE

Currently, intraoperative ultrasound in brain tumor surgery is a rapidly propagating option in imaging technology. We examined the accuracy and resolution limits of different ultrasound probes and the influence of 3D-reconstruction in a phantom and compared these results to MRI in an intraoperative setting (iMRI).

METHODS

An agarose gel phantom with predefined gel targets was examined with iMRI, a sector (SUS) and a linear (LUS) array probe with two-dimensional images. Additionally, 3D-reconstructed sweeps in perpendicular directions were made of every target with both probes, resulting in 392 measurements. Statistical calculations were performed, and comparative boxplots were generated.

RESULTS

Every measurement of iMRI and LUS was more precise than SUS, while there was no apparent difference in height of iMRI and 3D-reconstructed LUS. Measurements with 3D-reconstructed LUS were always more accurate than in 2D-LUS, while 3D-reconstruction of SUS showed nearly no differences to 2D-SUS in some measurements. We found correlations of 3D-reconstructed SUS and LUS length and width measurements with 2D results in the same image orientation.

CONCLUSIONS

LUS provides an accuracy and resolution comparable to iMRI, while SUS is less exact than LUS and iMRI. 3D-reconstruction showed the potential to distinctly improve accuracy and resolution of ultrasound images, although there is a strong correlation with the sweep direction during data acquisition.

Retrospective study comparing model-based deformation correction to intraoperative magnetic resonance imaging for image-guided neurosurgery

Brain shift during tumor resection compromises the spatial validity of registered preoperative imaging data that is critical to image-guided procedures. One current clinical solution to mitigate the effects is to reimage using intraoperative magnetic resonance (iMR) imaging. Although iMR has demonstrated benefits in accounting for preoperative-to-intraoperative tissue changes, its cost and encumbrance have limited its widespread adoption. While iMR will likely continue to be employed for challenging cases, a cost-effective model-based brain shift compensation strategy is desirable as a complementary technology for standard resections. We performed a retrospective study of [Formula: see text] tumor resection cases, comparing iMR measurements with intraoperative brain shift compensation predicted by our model-based strategy, driven by sparse intraoperative cortical surface data. For quantitative assessment, homologous subsurface targets near the tumors were selected on preoperative MR and iMR images. Once rigidly registered, intraoperative shift measurements were determined and subsequently compared to model-predicted counterparts as estimated by the brain shift correction framework. When considering moderate and high shift ([Formula: see text], [Formula: see text] measurements per case), the alignment error due to brain shift reduced from [Formula: see text] to [Formula: see text], representing [Formula: see text] correction. These first steps toward validation are promising for model-based strategies.